中文摘要：

城市化是过去一个多世纪以来世界的发展趋势,城市化显著改变城市地区土地利用/覆被,并引起诸如水资源短缺,洪水灾害加重,水环境恶化,生态系统退化等负面效应,如何更加准确估算城市化引起的土地利用/覆被变化不仅是研究城市化过程特征的需要,也是研究城市化所引起的各种效应的需要,并且一直是国际遥感和应用界的研究热点和难点。东莞市是改革开放以来我国城市化速度最快的城市。为了给研究东莞市城市化过程及其各种效应提供高精度且完整的城市化过程的长系列土地利用/覆被变化数据,基于1987～2015年间12期Landsat遥感影像,采用SVM算法对东莞市土地利用/土地覆被变化数据进行了自动分类,并对分类误差来源进行了分析总结,提出了自动分类结果后处理方法,制备了东莞市城市化过程土地利用/覆被变化数据。12期遥感影像自动分类的总体精度为81.37%,Kappa系数为0.75;最终结果总体精度为86.87%,Kappa系数为0.83。通过土地利用变化特征分析,将东莞市城市化过程以1996年和2005年为节点,划分为起步发展、快速发展和稳定发展3个阶段。

英文摘要：

Urbanization is the world developing trend in the past century,which significantly changed the land use/cover of the urbanized area,and caused a series negative impacts,such as water shortage,flood increase,environment pollution,ecosystem degradation.How to estimate the land use/cover change more accurately has the prerequisite of studying the urbanization processes and its impacts,and is the research hot and challenge of the remote sensing and application communities.Dongguan city expressed the rapidest urbanization in China since China＇s reform and opening door,and transferred from an agriculture county to a modern international metropolitan in less than 30 years,which has made a miracle in the world urbanization process.To prepare a high accuracy land use/cover change dataset for studying Dongguan＇s urbanization process and its impacts,this paper first estimated the land use/cover change dataset by employing Support Vector Machine auto-classification algorithm based on 12 Landsat remote sensing imageries from 1987 to2015 at an average interval of 3 year.Then the error sources is analyzed by comparing the results estimated by using auto-classification algorithm and visual interpretation,and a post data processing algorithm is proposed for refining the auto-classification results.The final dataset of land use/cover change of Dongguan City is produced with the above method with an average accuracy of 86.87% and a Kappa coefficient of0.83,which implies this product has a very good accuracy for analyzing the urbanization process of Dongguan city and its impacts.